rf coherent massive mimo a better ran alternative for 4g

RF Coherent Massive MIMO A Better RAN Alternative for 4G and 5G

Mihai Banu, CTO, Blue Danube Systems

July 5, 2019 | Blue Danube Systems | EXTERNAL | 1

Outline

1. Brief review of conventional Digital Massive MIMO

2. Fundamental flaws of Digital Massive MIMO

3. Array RF coherency and True 3D Beams to the rescue

4. Blue Danube economical Coherent Massive MIMO

5. MIMO technology evolution map and conclusions


Generic MIMO System Architecture

• “Digital” Radio Chains❑ ADC/DAC pairs + supporting analog/RF/digital circuitry

❑ Each radio chain has at least one RF Stage

❑ Each RF Stage connected to at least one antenna

• Ports: Independent data pipes between Processor and Radio Chains

• Layers: Independent data streams between Base Station and UEs

• L ≤ channel degrees of freedom

• In general: L ≤ P ≤ N ≤ M ≤ T (very important for minimizing HW)

• SU-MIMO (layers to one UE) & MU-MIMO (layers to multiple UEs)

T

Antennas

L

LayersBaseband

Processor

N

ADC/DAC

Stages

M

RF

StagesP Ports

…

…

… …

UE1

UE2

UE3

Digital

Front

End

digital analog

Base StationL Layers


R Digital Radio

Digital

ProcessorP

Regular

MIMO

P

R

...R

R

up to 8 radios

Digital

Full-Array

Massive

MIMO

P

R R R R R R

R R R R R R

R R R R R R

......

......

......

. . .. . .

. . .

128 radios

Digital

Sub-Array

Massive

MIMO

P

R R R

R R R

R R R

......

......

......

. . .. . .

. . .

32 radios

Regular MIMO and Digital Massive MIMO

OEM Systems

Hybridization to Lower Cost

Brute Force Scaling


Digital Massive MIMO Concept

• P=N=M=T = Large number such as 64, 128, 256 …

• Proposed for TDD by Marzetta/Ashikhmin in 2010.

• The main goal is to make MU-MIMO feasible

• All antenna signals are digitized and processed in the digital domain

• “Digital” Massive MIMO has massive amount of analog/RF circuits

and it is very expensive!

T

Antennas

L

LayersBaseband

Processor

N

ADC/DAC

Stages

M

RF

StagesP Ports

…

…

… …

UE1

UE2

UE3

Digital

Front

End

digital analog

Base StationL Layers


Motivation for Digital Massive MIMO

4 MU-MIMO Layers

Superimposed in RF Domain

4 MU-MIMO Layers

Separated In Digital Domain

(transmitted at RF)

(generated in digital domain)

▪ DSP-Based 3D Beamforming (BF)

▪ DSP-Based Multi-User MIMO (MU-MIMO)

both require

channel reciprocity!


Channel Sounding in TDD

UE

MIMO channel

including

the radio chains

.. .

received TDD pilots

measuring the channel

.. .

transmitted TDD pilots

aligned in phase

Downlink peaks (“beams”) and nulls (zeros, notches)

by Zero Forcing Algorithm


TDD Zero Forcing: Ideal Beam Placing

peak

Peak DSP-Based Beam

Layer 1 Layer 2

Layer 3 Layer 4


TDD Zero Forcing: Ideal Null Placing

zero zero

zero

Zero Notch Very Narrow Bandpass Filter

Layer 1 Layer 2

Layer 3 Layer 4


What’s in a Name?

That which we call a rose By any other name would smell as sweet!

(Romeo & Juliet)

Applying

Shakespeare’s genius

to Massive MIMO

An analog process By any other name (e.g. “Digital”) would be as tricky!


DSP-Based BF & MU-MIMO: Mostly Analog Schemes

DSPRadio

Array

UE

Channel + Transceiver Reciprocity

Channel Sounding

eNodeB

Analog signals & processing easily corrupted by noise and interference!

Digital signals & processing subject to “Garbage-In-Garbage-Out”

DSP Cannot Fix Major Errors in the Analog Portion of this Scheme!


Fundamental Flaws in Digital Massive MIMO

▪ Conventional Massive MIMO is designed for DSP-Based 3D BF & MU-MIMO

▪ DSP-Based techniques rely heavily on analog methods

❑ Channel sounding is an analog process

❑ Radio transceiver reciprocity is an analog design requirement

❑ Large # of radio chains yields a high content of analog & RF circuits

▪ What is digital in “Digital” Massive MIMO?

❑ Only digital computations for DSP-Based 3D beamforming

❑ Digital processing is subject to “Garbage-In-Garbage-Out”

▪ DSP-Based 3D Beamforming is highly vulnerable to inaccuracies in channel sounding and transceiver reciprocity

❑ Interference cancellation by Zero-Forcing algorithms is easily voided by real-world inaccuracies due to: mobility, interference & HW impairments.


The RF Coherency Difference - 2 GHz Band Example

0° RMS (0ps)

RF simulations with HFSS:

• 12x4 active array

• 0.5 λ (wavelength) horizontal spacing

• 0.7 λ vertical spacing

• Zero magnitude errors in all cases

150° RMS (204ps)

75° RMS (104ps)

25° RMS (35ps)

5° RMS (7ps) Necessary 3GPP HW Spec


TDD Zero Forcing Under Impairments

Layer 1 Layer 2

Layer 3 Layer 4



Layer 1 Layer 2

Layer 3 Layer 4


Tx/Rx Reciprocity Challenge in TDD Digital Massive MIMO

DACTx Chanel

FilterPA

Rx Chanel

FilterADC LNA

Tx phase shift & gain

Rx phase shift & gain

Tx/Rx Reciprocity conditions• Tx phase shift = Rx phase shift

• Tx gain = Rx gain

Tx/Rx Reciprocity difficult• PA/LNA very different circuits

• Tx/Rx filters different circuits

• ADC/DAC different circuits

• Tx/Rx do not track with T, etc.

• Local T changes rapidly due to

PA activity

Reciprocity errors in TDD equivalent to RF Coherency errors in FDD


Typical Tx/Rx Variations with T◦ (Measured Data)

-0.8

-0.6

-0.4

-0.2

0

0.2

0.4

0.6

0.8

35 40 45 50 55

RF Front-End Gain

0

5

10

15

20

25

35 40 45 50 55

RF Front-End Phase

Temp [°C] Temp [°C]

Phase [°]

Mag [d

B]

Tx

Rx

Tx

Rx

Tem

p [°C

]

Time = one month

Measured Temperature Across 12x4 Panel

Important Lesson: Aligning all Tx and all Rx within 5◦

rms is excellent for TDD Rx/Tx

reciprocity!

70

60

50

40

30


The Holy Grail of Wireless: True 3D Beams

What are True 3D Beams?

• Narrow EM radiation patterns also known as “Pencil Beams”

• Most radiated EM energy focused into a cone with little EM energy outside this cone

• Best use of EM spectrum (best SNR) for carrying information between two points

• Least amount of interference to others: Best for spectrum reuse!

• 5G targets extensive use of True 3D Beams


MU-MIMO by True 3D Beams

4 Layers Superimposed4 Layers Separated

(transmitted at RF)

(generated in digital domain)


Not All Beamforming Methods Are Created Equal!

DSP-Based Beamforming True 3D Beams


How Can We Generate True 3D Beams?

Dish Antenna Phased Array

▪ Beamforming by dish geometry

▪ Beam direction by mechanical

orientation

▪ Low cost but bulky, single beam,

not agile and not SW programable

▪ Beamforming by RF Coherency

▪ Beam direction by electrical phasing

(no mechanical movement)

▪ Very expensive but agile, multiple

beams and SW programmable


Classical Planar

Phased Array*

* www.radartutorial.eu

High Definition Active Antenna

System™ (HDAAS™)Commercial Deployment

of HDAAS™

Phase Array Cost

Breakthrough

by Blue Danube

Application

to 4G & 5G

First FDD Massive MIMO

October 2016

$$$$ $

Exclusive Low-Cost Phased Arrays in LTE Operation!


Blue Danube RF Coherency at 2 GHz

0° RMS (0ps)

RF simulations with HFSS:

• 12x4 active array

• 0.5 λ (wavelength) horizontal spacing

• 0.7 λ vertical spacing

• Zero magnitude errors in all cases

150° RMS (204ps)

75° RMS (104ps)

25° RMS (35ps)

5° RMS (7ps)

Phased Array Quality

Blue Danube 3GPP Spec


Shentel, US

Single site trial

24+ months, 2X gain

AT&T, US

Urban/Residential environment

100% capacity increase

Telstra, Australia

High traffic coverage

5x user throughput

Shentel, US

Multi-site trial

2.5X capacity gain,

time of day beam

adjustment

Phase-1: 2.1X capacity on 3 sector site

Phase-2: Adding panel on facing site

2016

2017

2018

Large Asian Operator

> 90% utilized sites

2.7X capacity gain,

3X traffic off-load,

vertical beam gainBeamCraft™ Product Family

AT&T, Mexico, Dense urban

Proven Performance in Commercial Networks


Reducing the Complexity of Digital Massive MIMO

Add ICs with ph/mag ctr.

Different C&M

Same aperture

Same # Layers

Less MU-MIMO Complexity

(LxM) data

N analog (LxM) radios

N radios

Add precise RF calibration

Digital Massive MIMOHDAASTypical 4G LTE MIMO


4x12 Array Boresight: Azimuth & ElevationSimulation and RF Scanner Measured Data

Uniform Taylor Taper


4x12 Array: Taylor in Azimuth & Elevation

Far field measured data (major antenna OEM) and HFSS simulation overlays


RF Energy

optimally

placed

Blue Danube

RF Placement Cloud SW

Blue Danube Smart RF Placement & Virtualization

ADC/DAC

Bank

RF

StagesPorts

…

…

… …

UE1

UE2

UE20Digital

Front

End

UE21

UE45

SON

EPC

BBUnon-uniform

trafficBlue Danube Hybrid Massive MIMO

▪ The baseline radiation pattern of each radio chain can be set

from the Cloud using ML and AI methods!

▪ All BBU processing is same as for any other MIMO system,

including Massive MIMO

TMx


Examples of Cloud-Programable Beam Patterns

Wide Beam

Narrow

Beam

Amoeba Beam V-Beam


Coherent Massive MIMO Upgrade Roadmap

Standard

4G BBU

Standard SON + Adaptive 3D beams matching traffic & clutter

Standard 4G/5G BBU/DU

with MU-MIMO

or Massive-MIMO DU

SW Upgrade SW Upgrade

Standard

5G DU

4G True 3D Beams

Flexible Sectorization

5G True 3D Beams

Flexible Sectorization

CPRI VRAN CPRI/VRAN

4G/5G MU-MIMO

with True 3D Beams

Upgrade Upgrade

same HDAAS on tower

Tower

Ground

Cloud


▪ Produces predictable True 3D Beams without channel sounding & DSP

❑ Avoids the fundamental flaws of standard Massive MIMO

✓ Far less performance degradation to real-world conditions: low SNIR, mobility, cluster deployment, number of users served

✓ Much better performance in FDD bands (lack of channel reciprocity)✓ Easy to generate vertical narrow beams for high-rises

❑ Best for MU-MIMO

✓ UE separation at RF before MU-MIMO processing

❑ Significant reduction in HW compared to standard Massive MIMO

✓ Lower cost, lower weight and lower power dissipation for FDD and TDD

▪ Enables easy cloud interference management: Real-Time RF placement

▪ Enables digital sub-band beamforming for hybrid architectures

RF Coherency Brings in Many Advantages


Four Key Parameters of MIMO Systems

1. Number of passive antennas

❑ Defines the array aperture, directly responsible for narrowest 3D beam possible

2. The resolution of the active array

❑ Number of subarrays that can be controlled independently in phase and magnitude

❑ The higher the resolution the smaller the side lobes

3. The number of digitizers in the active array

❑ “Digitizer” used here as synonymous term to “radio”, “digital radio” or “radio chain”

❑ Digitizers are expensive!

4. The number of data streams (Layers) that may be transmitted in parallel

❑ Layer is 3GPP terminology

❑ The more Layers the higher system capacity

R

...

. . .. . .

......

...

...

R

...

. . .. . .

......

...

...

. . .. . .

......

...

...

. . .. . .

......

...R

...

R

beam width

main beam

radio chains

Data 1

Data 2

Expensive

phase/mag

control

APERTURE

RESOLUTION

DIGITIZATION

LAYERS


Evolution of MIMO Systems for Cellular

Common

4G LTE MIMO

(Release 8-11)

Academic Research

“Marzetta”

Massive MIMO

Coherent

Massive MIMO

mmWave & sub 6 GHz

Sub 6 GHz

Digital Sub-Array

Massive MIMO

fixed

antenna

mapping

fixed

antenna

mappingfixed

sub-array

mapping dynamic

array

mapping

scalable

4G 5G

Blue Danube


Conclusions

1. Conventional Digital Massive MIMO has fundamental flaws

2. Array RF coherency avoids the fundamental flaws of Conventional Digital Massive MIMO

3. Digital signal processing alone cannot produce array RF coherency

4. Economical FDD Coherent Massive MIMO has been demonstrated


Thank You

rf coherent massive mimo a better ran alternative for 4g

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